Data Engineering Manager, Hinge Health

• Bachelor’s degree in Computer Science or related field, or equivalent professional experience
• 8+ years of experience in data engineering
• 2+ years of experience in a leadership or management role, leading a team of engineers
• Experience designing and building large-scale data pipelines and data warehouses
• Proficiency with SQL and at least one programming language (e.g., Python, Scala, Java)
• Proficiency in dbt and dimensional modeling
• Experience with cloud-based data technologies (e.g., AWS, Databricks, GCP, Azure)

Desirable

• We are seeking a highly skilled Data Engineering Manager to join our Data and Insights team at Hinge Health
• In this role, you will support our R&D department by leading a talented team of data engineers to design, build, and maintain scalable and reliable data models that power our products and analytics
• You will report to the Sr. Director of Data and Insights and work closely with cross-functional teams, including Product Management, Data Science, and other Engineering leaders
• This position is crucial in helping us navigate the complex landscape of healthcare data, contributing to the overall success of the company
• You will have a significant impact on our ability to leverage data for product innovation and operational excellence, with responsibilities spanning technical leadership, team management, and strategic contribution
• Your primary objectives will focus on execution, reliability, and growth
• You will drive the Data Engineering Verticals Roadmap, ensuring the development and delivery of data engineering solutions for vertical teams like Data Science and Product Growth, meeting all critical scaling milestones within your first six months
• Simultaneously, you will oversee the architectural evolution of pipelines and ETL/ELT processes to achieve 99.9% data availability and reliability for downstream teams within nine months
• In your first year, you will implement and enforce robust data governance and security standards—including HIPAA compliance—to measurably improve data quality and reduce risk
• Furthermore, you will manage and mentor the Data Engineering team, establishing clear career development paths and hiring key talent to meet capacity needs within six months
• You will be working within a robust technical environment using a stack that includes Python, SQL, dbt, Airflow, PostgreSQL, MySQL, REST, Aptible, Docker, Tonic.ai, Terraform, Spark, Kafka, Fivetran, Databricks, and AWS services such as S3, Lambda, Kinesis, RDS, and Glue. Our workflow is trunk-based CI/CD, and our security and compliance posture adheres to the highest standards of healthcare, including HIPAA, HITRUST, SOC 2, and CCPA
• Supervise a team of data engineers, including hiring, scheduling, assigning work, and reviewing performance
• Provide ongoing training, mentorship, and problem-solving assistance for your team members to foster their growth and development
• Lead the development and execution of the data engineering roadmap, ensuring it aligns with business goals
• Oversee the design, implementation, and maintenance of scalable and robust data pipelines and ETL/ELT processes
• Collaborate with data scientists, analysts, and product managers to understand data needs and deliver effective solutions
• Ensure the quality, reliability, and availability of data across the organization by establishing and enforcing data governance standards
• Drive the architectural vision for the data platform, making key decisions on technology and implementation
• Manage project priorities, deadlines, and deliverables for your team
• Architect and lead core data modeling initiatives. Architect our core data models. Provide technical leadership while guiding a team of expert modelers, ensuring scalable, reliable, and high-impact data foundations
• Leverage AI and LLMs. Investigate how LLMs and AI can change analytics and build data foundations that support these future needs. Focus on creating data marts optimized for LLMs and AI-driven analytics
• Employees in hybrid roles are required to be in the office 3 days per week, for the full 8 hours of a typical business day